TY - JOUR

T1 - Game-inspired Pedagogical Conversational Agents

T2 - A Systematic Literature Review

AU - Khosrawi-Rad, Bijan

AU - Grogorick, Linda

AU - Robra-Bissantz, Susanne

N1 - Publisher Copyright: © 2023, Association for Information Systems. All rights reserved.

PY - 2023

Y1 - 2023

N2 - Pedagogical conversational agents (PCAs) are an innovative way to help learners improve their academic performance via intelligent dialog systems. However, PCAs have not yet reached their full potential. They often fail because users perceive conversations with them as not engaging. Enriching them with game-based approaches could contribute to mitigating this issue. One could enrich a PCA with game-based approaches by gamifying it to foster positive effects, such as fun and motivation, or by integrating it into a game-based learning (GBL) environment to promote effects such as social presence and enable individual learning support. We summarize PCAs that are combined with game-based approaches under the novel term “game-inspired PCAs”. We conducted a systematic literature review on this topic, as previous literature reviews on PCAs either have not combined the topics of PCAs and GBL or have done so to a limited extent only. We analyzed the literature regarding the existing design knowledge base, the game elements used, the thematic areas and target groups, the PCA roles and types, the extent of artificial intelligence (AI) usage, and opportunities for adaptation. We reduced the initial 3,034 records to 50 fully coded papers, from which we derived a morphological box and revealed current research streams and future research recommendations. Overall, our results show that the topic offers promising application potential but that scholars and practitioners have not yet considered it holistically. For instance, we found that researchers have rarely provided prescriptive design knowledge, have not sufficiently combined game elements, and have seldom used AI algorithms as well as intelligent possibilities of user adaptation in PCA development. Furthermore, researchers have scarcely considered certain target groups, thematic areas, and PCA roles. Consequently, our paper contributes to research and practice by addressing research gaps and structuring the existing knowledge base.

AB - Pedagogical conversational agents (PCAs) are an innovative way to help learners improve their academic performance via intelligent dialog systems. However, PCAs have not yet reached their full potential. They often fail because users perceive conversations with them as not engaging. Enriching them with game-based approaches could contribute to mitigating this issue. One could enrich a PCA with game-based approaches by gamifying it to foster positive effects, such as fun and motivation, or by integrating it into a game-based learning (GBL) environment to promote effects such as social presence and enable individual learning support. We summarize PCAs that are combined with game-based approaches under the novel term “game-inspired PCAs”. We conducted a systematic literature review on this topic, as previous literature reviews on PCAs either have not combined the topics of PCAs and GBL or have done so to a limited extent only. We analyzed the literature regarding the existing design knowledge base, the game elements used, the thematic areas and target groups, the PCA roles and types, the extent of artificial intelligence (AI) usage, and opportunities for adaptation. We reduced the initial 3,034 records to 50 fully coded papers, from which we derived a morphological box and revealed current research streams and future research recommendations. Overall, our results show that the topic offers promising application potential but that scholars and practitioners have not yet considered it holistically. For instance, we found that researchers have rarely provided prescriptive design knowledge, have not sufficiently combined game elements, and have seldom used AI algorithms as well as intelligent possibilities of user adaptation in PCA development. Furthermore, researchers have scarcely considered certain target groups, thematic areas, and PCA roles. Consequently, our paper contributes to research and practice by addressing research gaps and structuring the existing knowledge base.

KW - Chatbot

KW - Education

KW - Game-based Learning

KW - Game-inspired Pedagogical Conversational Agent

KW - Gamification

KW - Literature Review

KW - Serious Game

KW - Virtual Companion

UR - http://www.scopus.com/inward/record.url?scp=85178626335&partnerID=8YFLogxK

U2 - 10.17705/1thci.00187

DO - 10.17705/1thci.00187

M3 - Journal articles

AN - SCOPUS:85178626335

VL - 15

SP - 146

EP - 192

JO - AIS Transactions on Human-Computer Interaction

JF - AIS Transactions on Human-Computer Interaction

SN - 1944-3900

IS - 2

M1 - 2

ER -